Relational databases are built for online transaction processing (OLTP) operations wherein many record-by-record searches and individual record insert and delete operations may be run in high volume processing environments. Data warehousing operations, by contrast, are heavily read-intensive and may draw on and process millions of database rows at a time. Because the controls and safeguards built into relational databases may cause processing overhead and bottlenecks, operations that process a large volume of database rows concurrently may be highly inefficient in consuming database resources and take excessive time to complete. The client-server aspect of relational database technology, while designed to protect databases and insure data integrity, may add processing overhead and significantly retard the speed of an operation drawing large volumes of data from multiple rows and tables. Performing large scale batch processing and data warehouse operations subject to the processing limitations and overhead of database may consume excessive processing resources and be disruptive of regular transaction processing activities.